I specialize in big data, natural language processing, and machine learning. My research interests focus on the application of artificial intelligence to improve economic policymaking.
I am interested improving policymaking by harnessing the power of data science. As a data manager at the Federal Reserve Board, I lead a team with a diverse project workload that includes research, policy, and operational data and software projects. My personal portfolio has strong research experience, technical expertise, and teaching materials. My research includes work on international trade, graph neural networks, natural language processing, and more. I am experienced with technologies such as Hadoop, Spark, Impala, TensorFlow, PyTorch, spaCy, NLTK, and R.Download Resume
MS in Data Science and Analytics, 2021
BA in Chemistry, Economics, Mathematics, 2017
I am the group manager for the Data Science and Application Development (DSAD) group, which serves as in-house experts in application design, automation, data science, big data, and AI for research, policy, and operational needs at the Federal Reserve Board. We host the Data Science and Engineering Hub in the Division of International Finance.
I lead of a team of 5 data scientists and application developers who manage applications and data that serve hundreds of internal staff. We contribute to the Board’s cloud adoption efforts and maintain many important climate, textual, and trade databases.
Please reach out to me if you want to talk about data science for economics!
Award can be received once in your career at the Federal Reserve Board and is awarded to 10-30 staff per year across the entire organization.
Award Description: “Anderson receives the award for his extraordinary initiative and innovation in advancing the Board’s data management and analytics capabilities. He worked across the Board and Federal Reserve System to promote innovative techniques and new technologies to change how analysts do their work. His efforts have made big-data analysis, machine learning, artificial intelligence, text analysis, and cloud computing more accessible to other staff, enabling these techniques to become integral parts of regular processes.”
Developed skills in data science, machine learning, and deep learning.
Majors in Chemistry, Economics, and Mathematics
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